Evaluation of an artificial intelligence U-net algorithm for pulmonary nodule tracking on chest computed tomography images.

ABSTRACT:

Objectives

To apply image registration in the follow up of lung nodules and verify the feasibility of automatic tracking of lung nodules using an artificial intelligence (AI) method.

Methods

For this retrospective, observational study, patients with pulmonary nodules 5-30 mm in diameter on computed tomography (CT) and who had at least six months follow-up were identified. Two radiologists defined a 'correct' cuboid circumscribing each nodule which was used to judge the success/failure of nodule tracking. An AI algorithm was applied in which a U-net type neural network model was trained to predict the deformation vector field between two examinations. When the estimated position was within a defined cuboid, the AI algorithm was judged a success.

Results

In total, 49 lu

SUBMITTER: Takeshita Y 

PROVIDER: S-EPMC10851735 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature